Since generative AI first rolled out to the masses, pro photographers and casual shutterbugs alike have speculated about its impact on image-making. Will AI finally make it so tha ...

AI systems often collect large amounts of data, sometimes without people even realizing their data is being collected. Here's ...

Many devices – including electric razors and toothbrushes – have become “AI-powered,” using machine learning algorithms to track how ... training data to create new content such as text or images.

Objective: Optical coherence tomography (OCT) images can visualize retinal layers and fundus lesions. Retinal structure segmentation is of great significance in early lesion detection and treatment ...

Mobile devices demonstrate performance degradation after 30 minutes of continuous operation, making long learning sessions impractical. The network infrastructure demand is 40% more than that for ...

Efficient on-device neural networks offer rapid, real-time, and interactive experiences while safeguarding private data from public internet exposure. Yet, the computational limitations of mobile ...

Mobile-Agents: Autonomous Multi-modal Mobile Device Agent. In the fast-paced world of mobile technology, a pioneering concept emerges as a standout: Large Language Models, especially Multimodal Large ...

New models in the EfficientViT family do semantic segmentation locally on the device. EfficientViT is built around a novel lightweight multi-scale attention module for hardware-efficient global ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...